White House Ramps Up Action as Anthropic Pauses Mythos Over Growing AI Security Fears

Anthropic’s decision to halt development of its Mythos large‑language model has forced the administration to move from a largely advisory posture to a more hands‑on coordination effort, according to a report from Chosunbiz. The White House, which has been monitoring the rapid proliferation of advanced foundation models, convened an inter‑agency task force within days of the pause, signaling “an accelerated response” to what officials described as “growing AI security fears.” The move reflects heightened concern that Mythos, which was touted as the most “psychologically settled” model after undergoing 20 hours of clinical psychiatry sessions, could exhibit unpredictable behavior when confronted with emotionally charged or contradictory prompts—a phenomenon the company itself labeled “behavioral drift” (AI on the Couch, Tashfia Akther).

The pause itself was announced by Anthropic in a brief statement that cited “security risks” without elaborating on technical specifics, a point echoed by RS Web Solutions, which reported that the company had suspended Mythos development pending a deeper risk assessment. The lack of detail has only amplified governmental anxiety, prompting senior officials to request a full technical review of the model’s architecture and training regimen. Sources close to the White House say the task force will draw on expertise from the National Institute of Standards and Technology, the Department of Defense’s Joint Artificial Intelligence Center, and the Office of Science and Technology Policy to evaluate whether Mythos’ novel reinforcement‑learning‑from‑human‑feedback (RLHF) techniques could be weaponized or cause systemic instability in downstream applications.

Industry observers note that Anthropic’s therapy‑inspired approach—documented in Akther’s “AI on the Couch” piece—was intended to mitigate exactly the kind of instability that now fuels security concerns. By subjecting the model to clinical techniques traditionally used to help humans regulate emotional responses, Anthropic hoped to embed a form of “psychological resilience” directly into the model’s weights. The resulting Mythos was marketed as a breakthrough in making LLMs less evasive, less sycophantic, and more robust under pressure. However, the same characteristics that make a model appear “settled” could also mask latent vulnerabilities, a nuance that regulators are now scrambling to understand.

The White House’s escalated involvement arrives at a moment when the broader AI ecosystem is wrestling with the balance between rapid innovation and safety oversight. The administration has already signaled a willingness to intervene in high‑risk AI projects, as evidenced by recent executive orders that call for mandatory risk assessments for models exceeding a certain capability threshold. By pulling Anthropic’s Mythos into the governmental spotlight, officials are testing the limits of those policies and gauging how quickly the private sector will cooperate with federal scrutiny. According to the Chosunbiz report, the task force is also exploring whether existing frameworks—such as the National AI Initiative Act—provide sufficient authority to compel Anthropic to share proprietary data or to enforce mitigation measures.

While Anthropic’s pause underscores the company’s own caution, it also raises questions about the competitive landscape. Rivals such as OpenAI and Google continue to push forward with increasingly capable models, many of which employ similar RLHF pipelines but have not yet subjected their systems to the kind of clinical “therapy” that Mythos underwent. If the White House’s response leads to stricter regulatory thresholds, developers may need to recalibrate their research timelines or adopt new safety protocols to avoid similar shutdowns. For now, the inter‑agency task force’s findings will likely shape the next wave of policy guidance, setting a precedent for how the United States addresses emergent security risks tied to the psychological engineering of AI.